Multiqc for JA19507 SA19202

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        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        About MultiQC

        This report was generated using MultiQC, version 1.6

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        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        Multiqc for JA19507 SA19202

        Multiqc report for Fastq files in job JA19507, run SA19202

        Report generated on 2020-02-13, 18:16 based on data in: /raida/gsafdata/jobinfo/qc/JA19507/SA19202/fastqc

        Welcome! Not sure where to start?   Watch a tutorial video   (6:06)

        General Statistics

        Showing 198/198 rows and 3/5 columns.
        Sample Name% Dups% GCM Seqs
        T-01-P1A01_S27_L001_R1_001
        21.3%
        42%
        2.3
        T-01-P1A01_S27_L002_R1_001
        21.3%
        42%
        2.3
        T-02-P1B01_S28_L001_R1_001
        22.2%
        42%
        1.9
        T-02-P1B01_S28_L002_R1_001
        22.3%
        42%
        1.8
        T-03-P1C01_S29_L001_R1_001
        21.0%
        42%
        1.5
        T-03-P1C01_S29_L002_R1_001
        21.0%
        42%
        1.5
        T-04-P1D01_S30_L001_R1_001
        21.3%
        42%
        2.0
        T-04-P1D01_S30_L002_R1_001
        21.2%
        42%
        1.9
        T-05-P1E01_S31_L001_R1_001
        24.5%
        44%
        2.0
        T-05-P1E01_S31_L002_R1_001
        24.2%
        44%
        2.0
        T-06-P1F01_S32_L001_R1_001
        22.0%
        42%
        2.2
        T-06-P1F01_S32_L002_R1_001
        22.1%
        42%
        2.2
        T-07-P1G01_S33_L001_R1_001
        23.0%
        42%
        1.9
        T-07-P1G01_S33_L002_R1_001
        23.0%
        42%
        1.8
        T-08-P1H01_S34_L001_R1_001
        23.5%
        42%
        2.2
        T-08-P1H01_S34_L002_R1_001
        23.1%
        42%
        2.1
        T-09-P1A02_S35_L001_R1_001
        21.6%
        42%
        2.5
        T-09-P1A02_S35_L002_R1_001
        21.4%
        42%
        2.4
        T-10-P1B02_S36_L001_R1_001
        21.8%
        43%
        2.0
        T-10-P1B02_S36_L002_R1_001
        21.7%
        43%
        2.0
        T-11-P1C02_S37_L001_R1_001
        22.4%
        42%
        2.0
        T-11-P1C02_S37_L002_R1_001
        22.2%
        42%
        2.0
        T-12-P1D02_S38_L001_R1_001
        21.9%
        42%
        2.0
        T-12-P1D02_S38_L002_R1_001
        21.8%
        42%
        2.0
        T-13-P1E02_S39_L001_R1_001
        22.4%
        43%
        1.7
        T-13-P1E02_S39_L002_R1_001
        22.2%
        43%
        1.7
        T-14-P1F02_S40_L001_R1_001
        21.5%
        42%
        2.2
        T-14-P1F02_S40_L002_R1_001
        21.2%
        42%
        2.1
        T-15-P1G02_S41_L001_R1_001
        21.9%
        43%
        1.6
        T-15-P1G02_S41_L002_R1_001
        21.7%
        43%
        1.6
        T-16-P1H02_S42_L001_R1_001
        20.8%
        43%
        2.1
        T-16-P1H02_S42_L002_R1_001
        20.6%
        43%
        2.1
        T-17-P1A03_S43_L001_R1_001
        21.3%
        42%
        2.1
        T-17-P1A03_S43_L002_R1_001
        21.2%
        42%
        2.0
        T-18-P1B03_S44_L001_R1_001
        21.0%
        42%
        1.8
        T-18-P1B03_S44_L002_R1_001
        20.7%
        42%
        1.7
        T-19-P1C03_S45_L001_R1_001
        22.1%
        42%
        1.6
        T-19-P1C03_S45_L002_R1_001
        22.1%
        42%
        1.6
        T-20-P1D03_S46_L001_R1_001
        23.7%
        41%
        2.1
        T-20-P1D03_S46_L002_R1_001
        23.4%
        42%
        2.1
        T-21-P1E03_S47_L001_R1_001
        18.8%
        43%
        1.4
        T-21-P1E03_S47_L002_R1_001
        18.6%
        43%
        1.3
        T-22-P1F03_S48_L001_R1_001
        22.5%
        42%
        2.0
        T-22-P1F03_S48_L002_R1_001
        22.1%
        42%
        2.0
        T-23-P1G03_S49_L001_R1_001
        21.9%
        42%
        1.7
        T-23-P1G03_S49_L002_R1_001
        21.8%
        42%
        1.7
        T-24-P1H03_S50_L001_R1_001
        22.0%
        42%
        2.3
        T-24-P1H03_S50_L002_R1_001
        22.0%
        42%
        2.2
        T-25-P1A04_S51_L001_R1_001
        21.3%
        42%
        2.4
        T-25-P1A04_S51_L002_R1_001
        21.3%
        42%
        2.3
        T-26-P1B04_S52_L001_R1_001
        22.5%
        42%
        2.2
        T-26-P1B04_S52_L002_R1_001
        22.4%
        42%
        2.2
        T-27-P1C04_S53_L001_R1_001
        21.2%
        42%
        2.0
        T-27-P1C04_S53_L002_R1_001
        21.0%
        42%
        1.9
        T-28-P1D04_S54_L001_R1_001
        21.0%
        43%
        2.0
        T-28-P1D04_S54_L002_R1_001
        20.9%
        43%
        2.0
        T-29-P1E04_S55_L001_R1_001
        22.6%
        42%
        2.0
        T-29-P1E04_S55_L002_R1_001
        22.6%
        42%
        2.0
        T-30-P1F04_S56_L001_R1_001
        21.5%
        42%
        1.9
        T-30-P1F04_S56_L002_R1_001
        21.2%
        42%
        1.9
        T-31-P1G04_S57_L001_R1_001
        20.7%
        43%
        1.7
        T-31-P1G04_S57_L002_R1_001
        20.7%
        43%
        1.7
        T-32-P1H04_S58_L001_R1_001
        20.4%
        42%
        2.1
        T-32-P1H04_S58_L002_R1_001
        20.1%
        42%
        2.1
        T-33-P1A05_S59_L001_R1_001
        21.1%
        42%
        2.7
        T-33-P1A05_S59_L002_R1_001
        21.0%
        42%
        2.6
        U-01-P1B05_S60_L001_R1_001
        21.2%
        43%
        2.8
        U-01-P1B05_S60_L002_R1_001
        21.2%
        43%
        2.8
        U-02-P1C05_S61_L001_R1_001
        24.3%
        42%
        2.9
        U-02-P1C05_S61_L002_R1_001
        24.0%
        42%
        2.8
        U-03-P1D05_S62_L001_R1_001
        24.3%
        42%
        3.2
        U-03-P1D05_S62_L002_R1_001
        24.3%
        42%
        3.1
        U-04-P1E05_S63_L001_R1_001
        24.7%
        43%
        2.9
        U-04-P1E05_S63_L002_R1_001
        24.6%
        43%
        2.8
        U-05-P1F05_S64_L001_R1_001
        23.6%
        43%
        2.9
        U-05-P1F05_S64_L002_R1_001
        23.5%
        43%
        2.8
        U-06-P1G05_S65_L001_R1_001
        22.9%
        43%
        2.6
        U-06-P1G05_S65_L002_R1_001
        22.5%
        43%
        2.6
        U-07-P1H05_S66_L001_R1_001
        23.3%
        43%
        3.2
        U-07-P1H05_S66_L002_R1_001
        23.0%
        43%
        3.1
        U-08-P1A06_S67_L001_R1_001
        21.9%
        43%
        2.9
        U-08-P1A06_S67_L002_R1_001
        21.7%
        43%
        2.9
        U-09-P1B06_S68_L001_R1_001
        23.1%
        42%
        3.3
        U-09-P1B06_S68_L002_R1_001
        23.1%
        42%
        3.2
        U-10-P1C06_S69_L001_R1_001
        26.8%
        42%
        3.4
        U-10-P1C06_S69_L002_R1_001
        26.5%
        42%
        3.4
        U-11-P1D06_S70_L001_R1_001
        21.5%
        43%
        2.8
        U-11-P1D06_S70_L002_R1_001
        21.3%
        43%
        2.7
        U-12-P1E06_S71_L001_R1_001
        22.4%
        42%
        3.1
        U-12-P1E06_S71_L002_R1_001
        22.2%
        42%
        3.0
        U-13-P1F06_S72_L001_R1_001
        23.1%
        42%
        3.0
        U-13-P1F06_S72_L002_R1_001
        23.2%
        42%
        3.0
        U-14-P1G06_S73_L001_R1_001
        22.1%
        42%
        2.6
        U-14-P1G06_S73_L002_R1_001
        22.1%
        42%
        2.5
        U-15-P1H06_S74_L001_R1_001
        24.4%
        43%
        3.2
        U-15-P1H06_S74_L002_R1_001
        24.2%
        43%
        3.2
        U-16-P1A07_S75_L001_R1_001
        22.8%
        43%
        3.6
        U-16-P1A07_S75_L002_R1_001
        22.8%
        43%
        3.5
        U-17-P1B07_S76_L001_R1_001
        25.0%
        42%
        3.3
        U-17-P1B07_S76_L002_R1_001
        24.9%
        42%
        3.2
        U-18-P1C07_S77_L001_R1_001
        24.4%
        43%
        2.7
        U-18-P1C07_S77_L002_R1_001
        24.3%
        43%
        2.6
        U-19-P1D07_S78_L001_R1_001
        21.9%
        43%
        2.7
        U-19-P1D07_S78_L002_R1_001
        21.7%
        43%
        2.6
        U-20-P1E07_S79_L001_R1_001
        23.6%
        43%
        3.4
        U-20-P1E07_S79_L002_R1_001
        23.4%
        43%
        3.4
        U-21-P1F07_S80_L001_R1_001
        23.6%
        42%
        2.8
        U-21-P1F07_S80_L002_R1_001
        23.5%
        42%
        2.7
        U-22-P1G07_S81_L001_R1_001
        25.4%
        42%
        3.6
        U-22-P1G07_S81_L002_R1_001
        25.3%
        42%
        3.5
        U-23-P1H07_S82_L001_R1_001
        22.9%
        43%
        2.8
        U-23-P1H07_S82_L002_R1_001
        22.7%
        43%
        2.8
        U-24-P1A08_S83_L001_R1_001
        24.3%
        43%
        4.0
        U-24-P1A08_S83_L002_R1_001
        23.8%
        43%
        3.9
        U-25-P1B08_S84_L001_R1_001
        24.2%
        43%
        3.3
        U-25-P1B08_S84_L002_R1_001
        24.0%
        43%
        3.3
        U-26-P1C08_S85_L001_R1_001
        21.0%
        42%
        2.7
        U-26-P1C08_S85_L002_R1_001
        21.0%
        42%
        2.6
        U-27-P1D08_S86_L001_R1_001
        23.8%
        42%
        3.2
        U-27-P1D08_S86_L002_R1_001
        23.7%
        42%
        3.2
        U-28-P1E08_S87_L001_R1_001
        26.2%
        42%
        3.2
        U-28-P1E08_S87_L002_R1_001
        26.3%
        42%
        3.1
        U-29-P1F08_S88_L001_R1_001
        25.3%
        43%
        2.9
        U-29-P1F08_S88_L002_R1_001
        25.2%
        43%
        2.9
        U-30-P1G08_S89_L001_R1_001
        25.1%
        42%
        2.8
        U-30-P1G08_S89_L002_R1_001
        25.0%
        42%
        2.7
        U-31-P1H08_S90_L001_R1_001
        22.7%
        42%
        3.2
        U-31-P1H08_S90_L002_R1_001
        22.6%
        42%
        3.1
        U-32-P1A09_S91_L001_R1_001
        26.7%
        43%
        3.4
        U-32-P1A09_S91_L002_R1_001
        26.7%
        43%
        3.3
        U-33-P1B09_S92_L001_R1_001
        24.8%
        43%
        3.2
        U-33-P1B09_S92_L002_R1_001
        24.7%
        43%
        3.1
        V-01-P1C09_S93_L001_R1_001
        25.7%
        42%
        2.4
        V-01-P1C09_S93_L002_R1_001
        25.4%
        42%
        2.4
        V-02-P1D09_S94_L001_R1_001
        25.9%
        42%
        2.4
        V-02-P1D09_S94_L002_R1_001
        25.7%
        42%
        2.4
        V-03-P1E09_S95_L001_R1_001
        26.3%
        42%
        2.4
        V-03-P1E09_S95_L002_R1_001
        26.2%
        42%
        2.4
        V-04-P1F09_S96_L001_R1_001
        25.2%
        42%
        2.5
        V-04-P1F09_S96_L002_R1_001
        24.8%
        42%
        2.5
        V-05-P1G09_S97_L001_R1_001
        22.7%
        43%
        1.9
        V-05-P1G09_S97_L002_R1_001
        22.6%
        43%
        1.9
        V-06-P1H09_S98_L001_R1_001
        25.2%
        42%
        2.7
        V-06-P1H09_S98_L002_R1_001
        25.2%
        42%
        2.7
        V-07-P1A10_S99_L001_R1_001
        24.1%
        42%
        2.5
        V-07-P1A10_S99_L002_R1_001
        24.1%
        42%
        2.4
        V-08-P1B10_S100_L001_R1_001
        24.9%
        41%
        2.7
        V-08-P1B10_S100_L002_R1_001
        24.8%
        41%
        2.6
        V-09-P1C10_S101_L001_R1_001
        22.7%
        41%
        2.3
        V-09-P1C10_S101_L002_R1_001
        22.4%
        42%
        2.2
        V-10-P1D10_S102_L001_R1_001
        23.6%
        41%
        2.7
        V-10-P1D10_S102_L002_R1_001
        23.3%
        41%
        2.6
        V-11-P1E10_S103_L001_R1_001
        22.7%
        42%
        2.1
        V-11-P1E10_S103_L002_R1_001
        22.6%
        42%
        2.1
        V-12-P1F10_S104_L001_R1_001
        22.5%
        42%
        2.1
        V-12-P1F10_S104_L002_R1_001
        22.5%
        42%
        2.1
        V-13-P1G10_S105_L001_R1_001
        22.2%
        42%
        1.8
        V-13-P1G10_S105_L002_R1_001
        22.0%
        42%
        1.8
        V-14-P1H10_S106_L001_R1_001
        23.0%
        42%
        2.4
        V-14-P1H10_S106_L002_R1_001
        22.7%
        42%
        2.3
        V-15-P1A11_S107_L001_R1_001
        24.5%
        43%
        2.6
        V-15-P1A11_S107_L002_R1_001
        24.3%
        43%
        2.6
        V-16-P1B11_S108_L001_R1_001
        21.1%
        42%
        2.6
        V-16-P1B11_S108_L002_R1_001
        21.0%
        42%
        2.5
        V-17-P1C11_S109_L001_R1_001
        21.9%
        43%
        1.8
        V-17-P1C11_S109_L002_R1_001
        21.8%
        43%
        1.8
        V-18-P1D11_S110_L001_R1_001
        21.7%
        42%
        2.1
        V-18-P1D11_S110_L002_R1_001
        21.5%
        42%
        2.0
        V-19-P1E11_S111_L001_R1_001
        19.0%
        43%
        1.7
        V-19-P1E11_S111_L002_R1_001
        19.2%
        43%
        1.7
        V-20-P1F11_S112_L001_R1_001
        22.1%
        43%
        2.5
        V-20-P1F11_S112_L002_R1_001
        21.9%
        43%
        2.4
        V-21-P1G11_S113_L001_R1_001
        22.4%
        42%
        1.8
        V-21-P1G11_S113_L002_R1_001
        22.3%
        42%
        1.8
        V-22-P1H11_S114_L001_R1_001
        24.3%
        42%
        2.6
        V-22-P1H11_S114_L002_R1_001
        24.0%
        42%
        2.5
        V-23-P1A12_S115_L001_R1_001
        24.2%
        42%
        2.8
        V-23-P1A12_S115_L002_R1_001
        24.1%
        42%
        2.7
        V-24-P1B12_S116_L001_R1_001
        22.6%
        44%
        2.3
        V-24-P1B12_S116_L002_R1_001
        22.4%
        44%
        2.2
        V-25-P1C12_S117_L001_R1_001
        22.7%
        43%
        2.8
        V-25-P1C12_S117_L002_R1_001
        22.5%
        43%
        2.7
        V-26-P1D12_S118_L001_R1_001
        23.1%
        42%
        2.7
        V-26-P1D12_S118_L002_R1_001
        23.0%
        42%
        2.7
        V-27-P1E12_S119_L001_R1_001
        25.6%
        42%
        2.5
        V-27-P1E12_S119_L002_R1_001
        25.3%
        42%
        2.4
        V-28-P1F12_S120_L001_R1_001
        25.0%
        42%
        2.4
        V-28-P1F12_S120_L002_R1_001
        24.7%
        42%
        2.4
        V-29-P1G12_S121_L001_R1_001
        22.5%
        43%
        2.4
        V-29-P1G12_S121_L002_R1_001
        22.3%
        43%
        2.4
        V-30-P1H12_S122_L001_R1_001
        23.5%
        42%
        2.7
        V-30-P1H12_S122_L002_R1_001
        23.7%
        42%
        2.6
        V-31-P2A01_S123_L001_R1_001
        32.1%
        42%
        5.2
        V-31-P2A01_S123_L002_R1_001
        32.1%
        42%
        5.1
        V-32-P2B01_S124_L001_R1_001
        29.4%
        42%
        3.7
        V-32-P2B01_S124_L002_R1_001
        29.3%
        42%
        3.6
        V-33-P2C01_S125_L001_R1_001
        28.1%
        42%
        3.2
        V-33-P2C01_S125_L002_R1_001
        28.3%
        42%
        3.1

        FastQC

        FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

        Sequence Counts

        Sequence counts for each sample. Duplicate read counts are an estimate only.

        This plot show the total number of reads, broken down into unique and duplicate if possible (only more recent versions of FastQC give duplicate info).

        You can read more about duplicate calculation in the FastQC documentation. A small part has been copied here for convenience:

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Quality Histograms
        198
        0
        0

        The mean quality value across each base position in the read.

        To enable multiple samples to be plotted on the same graph, only the mean quality scores are plotted (unlike the box plots seen in FastQC reports).

        Taken from the FastQC help:

        The y-axis on the graph shows the quality scores. The higher the score, the better the base call. The background of the graph divides the y axis into very good quality calls (green), calls of reasonable quality (orange), and calls of poor quality (red). The quality of calls on most platforms will degrade as the run progresses, so it is common to see base calls falling into the orange area towards the end of a read.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Sequence Quality Scores
        198
        0
        0

        The number of reads with average quality scores. Shows if a subset of reads has poor quality.

        From the FastQC help:

        The per sequence quality score report allows you to see if a subset of your sequences have universally low quality values. It is often the case that a subset of sequences will have universally poor quality, however these should represent only a small percentage of the total sequences.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Base Sequence Content
        0
        0
        198

        The proportion of each base position for which each of the four normal DNA bases has been called.

        To enable multiple samples to be shown in a single plot, the base composition data is shown as a heatmap. The colours represent the balance between the four bases: an even distribution should give an even muddy brown colour. Hover over the plot to see the percentage of the four bases under the cursor.

        To see the data as a line plot, as in the original FastQC graph, click on a sample track.

        From the FastQC help:

        Per Base Sequence Content plots out the proportion of each base position in a file for which each of the four normal DNA bases has been called.

        In a random library you would expect that there would be little to no difference between the different bases of a sequence run, so the lines in this plot should run parallel with each other. The relative amount of each base should reflect the overall amount of these bases in your genome, but in any case they should not be hugely imbalanced from each other.

        It's worth noting that some types of library will always produce biased sequence composition, normally at the start of the read. Libraries produced by priming using random hexamers (including nearly all RNA-Seq libraries) and those which were fragmented using transposases inherit an intrinsic bias in the positions at which reads start. This bias does not concern an absolute sequence, but instead provides enrichement of a number of different K-mers at the 5' end of the reads. Whilst this is a true technical bias, it isn't something which can be corrected by trimming and in most cases doesn't seem to adversely affect the downstream analysis.

        Click a sample row to see a line plot for that dataset.
        Rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content
        0
        0
        198

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content.

        From the FastQC help:

        This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.

        In a normal random library you would expect to see a roughly normal distribution of GC content where the central peak corresponds to the overall GC content of the underlying genome. Since we don't know the the GC content of the genome the modal GC content is calculated from the observed data and used to build a reference distribution.

        An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Per Base N Content
        198
        0
        0

        The percentage of base calls at each position for which an N was called.

        From the FastQC help:

        If a sequencer is unable to make a base call with sufficient confidence then it will normally substitute an N rather than a conventional base call. This graph shows the percentage of base calls at each position for which an N was called.

        It's not unusual to see a very low proportion of Ns appearing in a sequence, especially nearer the end of a sequence. However, if this proportion rises above a few percent it suggests that the analysis pipeline was unable to interpret the data well enough to make valid base calls.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Sequence Length Distribution
        198
        0
        0

        All samples have sequences of a single length (101bp).

        Sequence Duplication Levels
        196
        2
        0

        The relative level of duplication found for every sequence.

        From the FastQC Help:

        In a diverse library most sequences will occur only once in the final set. A low level of duplication may indicate a very high level of coverage of the target sequence, but a high level of duplication is more likely to indicate some kind of enrichment bias (eg PCR over amplification). This graph shows the degree of duplication for every sequence in a library: the relative number of sequences with different degrees of duplication.

        Only sequences which first appear in the first 100,000 sequences in each file are analysed. This should be enough to get a good impression for the duplication levels in the whole file. Each sequence is tracked to the end of the file to give a representative count of the overall duplication level.

        The duplication detection requires an exact sequence match over the whole length of the sequence. Any reads over 75bp in length are truncated to 50bp for this analysis.

        In a properly diverse library most sequences should fall into the far left of the plot in both the red and blue lines. A general level of enrichment, indicating broad oversequencing in the library will tend to flatten the lines, lowering the low end and generally raising other categories. More specific enrichments of subsets, or the presence of low complexity contaminants will tend to produce spikes towards the right of the plot.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Overrepresented sequences
        0
        198
        0

        The total amount of overrepresented sequences found in each library.

        FastQC calculates and lists overrepresented sequences in FastQ files. It would not be possible to show this for all samples in a MultiQC report, so instead this plot shows the number of sequences categorized as over represented.

        Sometimes, a single sequence may account for a large number of reads in a dataset. To show this, the bars are split into two: the first shows the overrepresented reads that come from the single most common sequence. The second shows the total count from all remaining overrepresented sequences.

        From the FastQC Help:

        A normal high-throughput library will contain a diverse set of sequences, with no individual sequence making up a tiny fraction of the whole. Finding that a single sequence is very overrepresented in the set either means that it is highly biologically significant, or indicates that the library is contaminated, or not as diverse as you expected.

        FastQC lists all of the sequences which make up more than 0.1% of the total. To conserve memory only sequences which appear in the first 100,000 sequences are tracked to the end of the file. It is therefore possible that a sequence which is overrepresented but doesn't appear at the start of the file for some reason could be missed by this module.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).


        Adapter Content
        198
        0
        0

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position.

        Note that only samples with ≥ 0.1% adapter contamination are shown.

        There may be several lines per sample, as one is shown for each adapter detected in the file.

        From the FastQC Help:

        The plot shows a cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. Once a sequence has been seen in a read it is counted as being present right through to the end of the read so the percentages you see will only increase as the read length goes on.

        Flat image plot. Toolbox functions such as highlighting / hiding samples will not work (see the docs).